An improved YOLOv5 infrared image algorithm for depression diagnosis

Wenhao Zhu; Jingyu Wan; Haowen Luo; Yuxing Mao

doi:10.1117/12.3036741

13 July 2024 An improved YOLOv5 infrared image algorithm for depression diagnosis

Wenhao Zhu, Jingyu Wan, Haowen Luo, Yuxing Mao

Proceedings Volume 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024); 132081J (2024) https://doi.org/10.1117/12.3036741
Event: 3rd International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 2024, Nanchang, China

Abstract

Depression poses significant threats to individuals’ health and even life safety. However, once accurately diagnosed, patients can receive effective treatment. Currently, screening for depression primarily involves questionnaire assessments, blood biochemical tests, and imaging studies, but the definitive diag- nosis is determined by questionnaire assessments, with blood biochemical tests and imaging studies serving as supplementary diagnostic methods. Recent advancements in medical research have revealed that various emotions can trigger specific physio- logical, biochemical, and behavioral responses. These responses, through underlying muscle activity and microvascular circulation changes, alter body temperature distribution, thus positioning body temperature distribution as a potential indicator for de- tecting somatization disorders related to depression, offering a new perspective for imaging studies. This article introduces a diagnostic model for somatization depression and anxiety disorders based on infrared images by training with human body images captured by an infrared thermal imager and utilizing an improved YOLOv5 algorithm for human body part detection, followed by extracting lesion features for secondary classification. Testing has shown that this algorithm has a high accuracy rate of 82% in screening for depression. As a means of assisting in the diagnosis of depression, such a combination of imaging studies and deep learning not only achieves real-time detection but also significantly reduces the workload of doctors

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wenhao Zhu, Jingyu Wan, Haowen Luo, and Yuxing Mao "An improved YOLOv5 infrared image algorithm for depression diagnosis", Proc. SPIE 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 132081J (13 July 2024); https://doi.org/10.1117/12.3036741

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KEYWORDS

Thermal modeling

Infrared imaging

Infrared radiation

Thermography

Data modeling

Diagnostics

Education and training

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